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Diabetes Monitoring System
Published in Rajarshi Gupta, Dwaipayan Biswas, Health Monitoring Systems, 2019
Recently, Turksoy et al. [2] introduced a multi-module multivariable adaptive control strategy for artificial pancreas for type 1 diabetes. The artificial pancreas collects information from many sensors, computes the optimal insulin amount to be infused, and then manipulates the infusion rate of the pump. A recursive model of glucose concentration dynamics is first estimated using the ARMAX method of system identification. The controller takes various inputs like: Glucose and activity feedbackHypoglycemia detection and carbohydrates suggestionMeal detection and hyperglycemia preventionExercise classificationFault detection and diagnosis
Biomedical Devices: Overview
Published in Jack Wong, Raymond K. Y. Tong, Handbook of Medical Device Regulatory Affairs in Asia, 2018
Glucose monitoring is essential for diabetes management. LifeScan, J&J company One Touch Ultralink blood glucose monitoring system allows accurate estimation of blood glucose [25]. In combination of an insulin pump, proper dosing can be administered in response to blood glucose level before or after meals. To streamline these processes, an artificial pancreas system helps reduce the severity of a drop in glucose levels by automatically adjusting insulin flow. The system combines a continuous glucose monitor, an insulin infusion pump, and a glucose meter [26].
Smart Healthcare and IoT Technologies
Published in Ankan Bhattacharya, Bappadittya Roy, Samarendra Nath Sur, Saurav Mallik, Subhasis Dasgupta, Internet of Things and Data Mining for Modern Engineering and Healthcare Applications, 2023
Vinaytosh Mishra, Somayya Madakam
Healthcare systems are facing unprecedented challenges such as the outbreak of infectious diseases, increased prevalence of chronic disease, shortage of doctors and clinicians, lack of timely medicines, ageing population, rising costs, etc. Hence, Healthcare systems worldwide should focus on better individualized care, improved population health, and lower healthcare cost. That means addressing these issues requires the use of smart health technologies that make healthcare more intelligent, distributed, and personalized. These advanced technologies like IoT smart devices, Edge (Fog) computing, artificial intelligence, and computer vision are shaping the landscape of the future of healthcare. Moreover, applied technologies like medical imaging (MI), bedside telemetry, and natural language processing (NLP) are augmenting the work of clinicians and hence enabling them to focus more on the human side of care. Among all, the Internet of Things technologies have been immensely used in healthcare. Internet of Things-enabled devices have made remote monitoring of patients possible and have many applications in managing chronic diseases and providing geriatric care. For example, a closed-loop system having a continuous glucose monitoring system (CGMS) and insulin pump can act as an artificial pancreas for a diabetes patient having insulin resistance and are a boon for Type-2 Diabetes Mellitus patients. IoT-enabled devices can generate an alarm in case of hypoglycaemia and save the life of a diabetic patient. IoT-enabled devices are used for performance monitoring of critical medical equipment and raise alarm or notify the care provider when preventive maintenance is required. Bluetooth-enabled proximity tracking apps have also been found very helpful in contact tracing during the recent outbreak of COVID-19 disease. Besides this, IoT also has other non-clinical applications such as hospital environment monitoring through closed-circuit television (CCTV)/internet protocol (IP) camera, inventory management, and theft detection round the clock.
Auto adaptation of closed-loop insulin delivery system using continuous reward functions and incremental discretization
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2023
Maria Cecilia Serafini, Nicolas Rosales, Fabricio Garelli
According to recent studies, there are more than 8 million people worldwide living with Type 1 Diabetes Mellitus (T1DM) (Gregory et al. 2022). Current treatments allow people who live with T1DM to remain within the limits of normoglycemia ( mg/dl) for most of the time with the aid of exogenous insulin injection. One way to administer insulin is through manual injections multiple times a day (MDI- Multiple Daily Injections), or through insulin pumps known as Continuous Subcutaneous Insulin Infusion (CSII). The integration of CSII with Continuous Glucose Monitoring (CGM) devices has enabled research of automatic control of insulin infusion, resulting in the development of the Artificial Pancreas Systems (APS) (Lewis 2021). APS are also referred to as Automated Insulin Delivery systems (AIDs) or Fully Automated Insulin Delivery Systems (fAIDs), depending on whether they use hybrid or closed-loop controllers.
Robust stability control for nonlinear time varying delay fractional order practical systems and application in Glucose-Insulin system
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2022
Gholamreza Alikhani, Saeed Balochian
The global prevalence of diabetes mellitus has risen dramatically in recent years (Jamaludin et al. 2018). The management of this condition is critical in clinical treatments to avoid an increase in mortality. Controlling this disease is critical because of this issue. Blood glucose control with exogenous insulin injection is a complicated nonlinear control problem (Rigatos et al. 2017). Controlling blood glucose levels accurately is critical for the treatment of diabetics as well as patients in centralized clinical units (Mandal and Sutradhar 2017). Diabetic patients can be treated by keeping their blood glucose levels within the allowable range with the help of insulin injection management, but this takes time because the injected insulin needs time to absorb peripheral glucose. As a result, there is always a time lag between the levels of plasma glucose and interstitial glucose (Mandal and Sutradhar 2017). The impact of this delay is examined in this research. External insulin should be injected to keep blood glucose levels within the desired range (70–180 mg/dL), and a closed-loop control system is necessary to inject insulin at the right pace (Soylu and Danişman 2018). A glucose sensor, a controller, and an insulin pump comprise the closed-loop control system, also known as the artificial pancreas. Glucose sensor signals are sent to the controller, which employs a control algorithm to keep insulin within a safe range. Ideally, an insulin pump is used.
Co-creation in support of responsible research and innovation: an analysis of three stakeholder workshops on nanotechnology for health
Published in Journal of Responsible Innovation, 2022
Sikke R. Jansma, Anne M. Dijkstra, Menno D.T. de Jong
In the exploration phase, participants introduced themselves, and the specific topic of the co-creation workshop was presented. In the co-creation workshop on diabetes, two representatives from different technological start-ups presented their products. One product was an artificial pancreas, which is a device for diabetes type 1 patients that continuously monitors the blood and automatically injects insulin when needed. The other product was an early diagnostic device that can detect diabetes type 2 at an early stage before any symptoms occur. In the co-creation workshop on sensor technologies, a scientist presented her research on sensors for better detection of cancer through proteins. In the policy-related co-creation workshop, there was no focus on a specific technology or research. Instead, the moderator introduced the question to the participants about how to increase RRI by integrating societal needs and values in product- and research development in nanotechnologies for health.